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[Other] Show HN: Fast Tor Onion Service vanity address generator Hello,<p>I&#x27;ve built the tool to generate vanity Tor Onion Service addresses:<p><pre><code> $ onion-vanity-address allium Found allium... in 12s after 558986486 attempts (48529996 attempts&#x2F;s) --- hostname: alliumdye3it7ko4cuftoni4rlrupuobvio24ypz55qpzjzpvuetzhyd.onion hs_ed25519_public_key: PT0gZWQyNTUxOXYxLXB1YmxpYzogdHlwZTAgPT0AAAAC1ooweCbRP6ncFQs3NRyK40fRwaodrmH572D8py+tCQ== hs_ed25519_secret_key: PT0gZWQyNTUxOXYxLXNlY3JldDogdHlwZTAgPT0AAAAQEW4Rhot7oroPaETlAEG3GPAntvJ1agF2c7A2AXmBW3WqAH0oUZ1hySvvZl3hc9dSAIc49h1UuCPZacOWp4vQ </code></pre> The tool checks ~45&#x27;000&#x27;000 keys per second on a laptop which is ~2x faster than widely-used mkp224o <a href="https:&#x2F;&#x2F;github.com&#x2F;cathugger&#x2F;mkp224o" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;cathugger&#x2F;mkp224o</a><p>I&#x27;ve explained key performance difference here <a href="https:&#x2F;&#x2F;github.com&#x2F;AlexanderYastrebov&#x2F;onion-vanity-address?tab=readme-ov-file#the-fastest-search-algorithm" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;AlexanderYastrebov&#x2F;onion-vanity-address?t...</a><p>Would love your feedback, thanks!

[Other] Show HN: Runner – the anti-vibe coding agent Now that AI is capable of writing large volumes of production-quality code, our role as developers is changing. Our primary job is no longer writing code. It’s planning and communicating software design and architecture. We have to do this collaboratively with agents and then review and iterate on their implementations.<p>IDEs were not built for this workflow. So about three months ago I decided to try to build what I thought this new interface should look like.<p>Runner is a coding agent purpose-built for this new “plan and review” workflow. It’s not for vibe coding. It’s for professional software developers who are responsible for the code they ship.<p>It encourages and supports a more structured and controlled workflow than other coding agents. It’s built around the concept of tasks. A task is a small, clearly scoped change. The planning agent creates and edits task specs, and then you can assign them to coding agents once you’re happy with the plan. When the coding agent finishes, you can review the changes via the built-in diff viewer. If you’re happy with them you can approve the changes, which will trigger a git commit.<p>Runner is available as a free BYOK beta for MacOS right now. You can learn more and download it here: <a href="https:&#x2F;&#x2F;runnercode.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;runnercode.com&#x2F;</a>. You will need at least a Gemini API key, and for best performance also an OpenAI API key.

[CLI Tool] Show HN: Kafkatop, top-like CLI for Kafka Hey HN, for those of you tired of running kafka-consumer-groups.sh and similar tools, here&#x27;s a small real-time monitoring CLI tool for Apache Kafka, that displays consumer lag and event rates in a clean, top-like interface. You can quickly assess which consumers are lagging and when they will catch up.<p>I&#x27;ve made this to quickly assess the health of remote on-premises clusters which most of the time lack proper monitoring.<p>The tool can be found here: <a href="https:&#x2F;&#x2F;github.com&#x2F;sivann&#x2F;kafkatop" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;sivann&#x2F;kafkatop</a><p>I&#x27;d be very interested to hear your feedback or any features you think would add value to this tool!

[Other] A Web Framework for Zig

[Other] Show HN: I Built Davia–A New Way to Create Interactive Documents with Code I’ve been working on something called Davia — a platform for creating interactive documents.<p>These are “living documents”: each page is self-contained, combining editable content, interactive components, and data. You can read them, edit them, and actually interact with them — more like mini-apps than static docs.<p>Here’s what makes it interesting: The interactive components are pieces of code generated on the fly, so you’re not limited to a fixed set of blocks like in Notion. You can create infinitely flexible functionality right inside a doc. Technically, an interactive page is an ensemble of components (MDX file), data (JSON file), and a main HTML file — all bundled and compiled on the fly. This gives each document its own portable architecture. Once built, you can publish your doc either as a live site (with a custom URL and persistent interactions) or as an open-source template that others can import, remix, and build upon.<p>We’re building an open-source community around this. If people import your templates, you’ll be credited (and in beta, you can even earn from them). It’s free to use while we’re in beta, and I’d love to build it with you.<p>If you enjoy tinkering with small tools, pushing the limits of interactive docs, or want to explore new ways of sharing knowledge, this could be fun. Feedback, ideas, and contributions are more than welcome — join us in r&#x2F;davia_ai!

[Other] Show HN: Asxiv.org – Ask ArXiv papers questions through chat I built this yesterday to help understand papers I&#x27;m interested in. It&#x27;s using the gemini 2.5 flash lite model, but you can run it yourself[1] and switch to 2.5 pro for better results.<p>Happy to answer any questions or take suggestions on how I can improve it!<p>1. <a href="https:&#x2F;&#x2F;github.com&#x2F;montanaflynn&#x2F;asxiv" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;montanaflynn&#x2F;asxiv</a>

[Other] DeepCodeBench: Real-World Codebase Understanding by Q&A Benchmarking

[Other] Show HN: Flox – Nvidia CUDA available for the Nix ecosystem Hey Everyone! Ron here, part of the NixOS Foundation and building Flox. Just coming out of this years NixCon and pretty excited to show hn below :)<p>As of today, NVIDIA officially recognizes Canonical, SUSE, CIQ, and Nix—via Flox—as supported distributors for CUDA. Full blog - <a href="https:&#x2F;&#x2F;developer.nvidia.com&#x2F;blog&#x2F;developers-can-now-get-cuda-directly-from-their-favorite-third-party-platforms&#x2F;" rel="nofollow">https:&#x2F;&#x2F;developer.nvidia.com&#x2F;blog&#x2F;developers-can-now-get-cud...</a><p>This is a huge win for the Nix community. For years, CUDA on Nix was possible but painful—builds could take hours, and redistributing prebuilt binaries was blocked by NVIDIA&#x27;s licensing requirements.<p>NVIDIA&#x27;s growing engagement with key Linux distributions reflects the company&#x27;s evolution in working with open source communities. Now, for the first time, NVIDIA is allowing these vendors to package and serve the CUDA Toolkit and CUDA-accelerated packages directly from their package repositories.<p>That means Ubuntu users can get CUDA via `apt`, SUSE users via `zypper`, Rocky Linux users via `dnf`, and Nix users simply by declaring CUDA dependencies in their Nix expressions, `shell.nix` files, or flakes. Across all four platforms, developers can now pull in prebuilt, prepatched CUDA software—including huge packages like PyTorch, TensorFlow, TensorRT, OpenCV, ffmpeg, and more.<p>On Nix (my own bias showing), setup is straightforward: just add Flox&#x27;s cache as an `extra-substituter` in your `nix.conf` or `configuration.nix`.

[Other] Show HN: Ultraplot – A succint wrapper for matplotlib

[CLI Tool] Show HN: Llmswap – Universal AI SDK and Code Generation CLI I was constantly switching between my terminal and ChatGPT&#x2F;Claude&#x2F;Gemini for code help. Built llmswap 4.1.1 to fix this.<p>Now I just type: llmswap generate &quot;command I need&quot;<p>Real examples that save hours:<p>Site emergency - needed to debug compressed logs:<p>llmswap generate &quot;grep through gzipped nginx logs for errors&quot;<p>Got: zgrep -i &quot;error\|fail&quot; &#x2F;var&#x2F;log&#x2F;nginx&#x2F;*.gz | head -50<p>That regex everyone googles:<p>llmswap generate &quot;extract all IP addresses from log file&quot;<p>Got: grep -oE &#x27;([0-9]{1,3}\.){3}[0-9]{1,3}&#x27; access.log | sort | uniq -c<p>Complex configs? No problem:<p>llmswap generate &quot;docker compose for Prometheus Grafana monitoring&quot; &gt; stack.yml<p>80 lines of production-ready YAML.<p>The killer feature - works INSIDE vim:<p>:r !llmswap generate &quot;MongoDB create user with read&#x2F;write access&quot;<p>Got: db.createUser({user:&quot;appuser&quot;,pwd:&quot;password&quot;,roles:[{role:&quot;readWrite&quot;,db:&quot;myapp&quot;}]})<p>Code appears at cursor. No browser. No copy-paste.<p>Supports 8 providers (OpenAI, Claude, Gemini, Groq, IBM Watson, Ollama, etc). Use whatever API keys you already have. No additional subscriptions.<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;sreenathmmenon&#x2F;llmswap" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;sreenathmmenon&#x2F;llmswap</a><p>PyPI: <a href="https:&#x2F;&#x2F;pypi.org&#x2F;project&#x2F;llmswap&#x2F;" rel="nofollow">https:&#x2F;&#x2F;pypi.org&#x2F;project&#x2F;llmswap&#x2F;</a>

[Other] Show HN: Haystack – Review pull requests like you wrote them yourself Hi HN!<p>We’re Akshay and Jake. We put together a tool called Haystack to make pull requests straightforward to read.<p>What Haystack does:<p>-- Builds a clear narrative. Changes in Haystack aren’t just arranged as unordered diffs. Instead, they unfold in a logical order, each paired with an explanation in plain, precise language<p>-- Focuses attention where it counts. Routine plumbing and refactors are put into skimmable sections so you can spend your time on design and correctness<p>-- Provides full cross-file context. Every new or changed function&#x2F;variable is traced across the codebase, showing how it’s used beyond the immediate diff<p>Here’s a quick demo: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;w5Lq5wBUS-I" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;w5Lq5wBUS-I</a><p>If you’d like to give it a spin, head over to haystackeditor.com&#x2F;review! We set up some demo PRs that you should be able to understand and review even if you’ve never seen the repos before!<p>We used to work at big companies, where reviewing non-trivial pull requests felt like reading a book with its pages out of order. We would jump and scroll between files, trying to piece together the author’s intent before we could even start reviewing. And, as authors, we would spend time to restructure our own commits just to make them readable. AI has made this even trickier. Today it’s not uncommon for a pull request to contain code the author doesn’t fully understand themselves!<p>So, we built Haystack to help reviewers spend less time untangling code and more time giving meaningful feedback. We would love to hear about whether it gets the job done for you!<p>How we got here:<p>Haystack began as (yet another) VS Code fork where we experimented with visualizing code changes on a canvas. At first, it was a neat way to show how pieces of code worked together. But customers started laying out their entire codebase just to make sense of it. That’s when we realized the deeper problem: understanding a codebase is hard, and engineers need better ways to quickly understand unfamiliar code.<p>As we kept building, another insight emerged: with AI woven into workflows, engineers don’t always need to master every corner of a codebase to ship features. But in code review, deep and continuous context still matters, especially to separate what’s important to review from plumbing and follow-on changes.<p>So we pivoted. We took what we’d learned and worked closely with engineers to refine the idea. We started with simple code analysis (using language servers, tree-sitter, etc.) to show how changes relate. Then we added AI to explain and organize those changes and to trace how data moves through a pull request. Finally, we fused the two by empowering AI agents to use static analyses. Step by step, that became the Haystack we’re showing today.<p>We’d love to hear your thoughts, feedback, or suggestions!

[Other] ChatGPT Developer Mode: Full MCP client access

[Other] Show HN: Ark v0.5.0 – A Minimal, High-Performance Entity Component System for Go I’ve just released Ark v0.5.0, a lightweight Entity Component System (ECS) library for Go, built with a focus on performance and simplicity.<p>If you&#x27;re new to Ark: it&#x27;s a high-performance Go ECS library with a clean API and zero dependencies. Beyond its core ECS functionality, Ark stands out for ultra-fast batch operations and first-class support for entity relationships.<p>This release brings notable performance improvements to queries via smarter indexing, plus new methods for sampling random entities. The documentation has been expanded with a chapter on design philosophy and limitations, along with new examples covering advanced topics like entity relations, world locking, spatial indexing, and parallel simulations.<p>If you’re exploring ECS patterns in Go or looking for a an ECS that delivers performance without sacrificing usability, I’d love to hear your feedback. Contributions are welcome.<p>Changelog: github.com&#x2F;mlange-42&#x2F;ark&#x2F;blob&#x2F;main&#x2F;CHANGELOG.md

[API/SDK] Show HN: Robot MCP Server – Connect Any Language Model and ROS Robots Using MCP We’ve open-sourced the Robot MCP Server, a tool that lets large language models (LLMs) talk directly to robots running ROS1 or ROS2.<p>What it does - Connects any LLM to existing ROS robots via the Model Context Protocol (MCP) - Natural language → ROS topics, services, and actions (And the ability to read any of them back) - Works without changing robot source code<p>Why it matters - Makes robots accessible from natural language interfaces - Opens the door to rapid prototyping of AI-robot applications - We are trying to create a common interface for safe AI ↔ robot communication<p>This is too big to develop alone — we’d love feedback, contributors, and partners from both the robotics and AI communities.

[Package Manager] Show HN: Nixite – automatically install all your Linux software unattendedly Nixite generates a bash script to automatically install all your Linux software unattendedly. Nixite prevents prompts and picks the best installation method. Nixite supports Ubuntu-based systems and Arch-based systems. Nixite installs a nixite-updater script to update all package managers and software at once.

[Build/Deploy] Automate compile_flags for C/C++ projects on the Zig build system

[DevOps] Show HN: TailGuard – Bridge your WireGuard router into Tailscale via a container My elderly parents are behind a 5G connection in rural areas, and I help them manage their network from overseas. I found a reasonably priced 5G router that can do external antennas required for it to work, but the only reasonable ways to get access to it is either through OpenVPN or WireGuard, the latter of which is much more lightweight and preferred with the memory constraints of the device.<p>The problem with WireGuard is that it requires handling key management oneself, and configuring the keys to every device you want to access it from. It also doesn&#x27;t play nicely together with other VPNs, meaning I ended up connecting and disconnecting VPNs whenever I wanted to use them. This is especially evident on my phone, which only allows one VPN app at a time.<p>I was already using Tailscale as an easy way to handle homelab access with SSO, even if some computers are behind ISP CGNAT, and came up with this idea of spinning up a Docker container to connect the two. I found some suggestions for it online, but nothing ready to use. It ended up being more work than I expected to fine tune the routing, IPv6, firewall settings, re-resolving the DNS of the router on IP address changes etc.<p>I got it very stable eventually though, and wanted to share with everyone else. I think it&#x27;s cool to have the WireGuard router looking like any other Tailscale node in my tailnet now.

[Other] Show HN: Shellcast.tv – Stream your vibe coding

[Other] Show HN: Vicinae – a native, Raycast-compatible launcher for Linux Hi HN!<p>I’ve always been a fan of application launchers, and I was impressed by the approach the Raycast team took — especially their extension system. About six months ago I started building something similar for Linux, aiming to integrate deeply at the OS level and give extensions a lot of power.<p>Vicinae is written in C++ with Qt Widgets. I chose Widgets over QML for more imperative control of the UI, especially around extension handling. So far that’s worked well — modern C++ is great.<p>To support my goals I built a number of custom widgets, including a fully virtualized list that can efficiently render tens of thousands of items. That gave me a lot of respect for Qt — it’s a powerful framework that mostly stayed out of my way.<p>A key feature is support for Raycast extensions (React + TypeScript), most of which can be installed and used directly inside the launcher (though not all features are implemented yet). There’s also a native API package (@vicinae&#x2F;api) for writing Vicinae-specific extensions with additional capabilities. This required writing a custom React reconciler — surprisingly straightforward, though still unpolished.<p>Like Raycast, Vicinae ships with powerful built-in modules, but the goal isn’t to make a clone. I want it to grow into its own project that fits the FOSS model better, while staying compatible with the Raycast ecosystem. I also plan to bring it to other OSes eventually.<p>I’d love feedback on the technical approach, and suggestions for what would make this useful to you. Contributions are very welcome — I’ve already been pleasantly surprised by how quickly people started helping.<p>Docs: <a href="https:&#x2F;&#x2F;docs.vicinae.com" rel="nofollow">https:&#x2F;&#x2F;docs.vicinae.com</a> Repo: <a href="https:&#x2F;&#x2F;github.com&#x2F;vicinaehq&#x2F;vicinae" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;vicinaehq&#x2F;vicinae</a>

[Other] Show HN: Superagents – connect spreadsheets to any database, API or MCP server Hi HN, I’m Eoin, founder of Sourcetable (<a href="https:&#x2F;&#x2F;sourcetable.com" rel="nofollow">https:&#x2F;&#x2F;sourcetable.com</a>).<p>Today, we’re launching Superagents. You can now connect your spreadsheet to any database, API or MCP server on the Internet. All of that data is available inside your spreadsheet, and you can use AI to analyze it and build models, reports and visualizations.<p>The reason I started the company is because I spent 10 years at startups across engineering and operations roles and realized that Excel and Sheets weren&#x27;t architected for the modern information environment. This creates a tremendous amount of nuisance and busywork cobbling together SaaS tools, reporting suites, and the misery of endless coordination meetings to make it all happen. (Boo meetings!)<p>Spreadsheets aren’t just a business application: they’re the original thinking tool. The quality of these tools has a downstream impact on analytical thinking and creativity writ large, so this is a problem worth solving. Fast forward to today, we’re a 6 person team taking on Excel, Sheets and ChatGPT, so we’re excited to hear what you think!<p>Who are Superagents for? Analysts, operators, and anyone doing data-centric work in spreadsheets. We see a tonne of finance people, of course, but also students, researchers and mom &amp; pop shops. Sourcetable&#x27;s superagents democratize data access and analysis, which is nice because our company’s mission is to make data accessible to everyone.<p>Why “Superagents”? Because they can plan and orchestrate other task-specific agents to complete your work for you. We have a lot of different AI tools and agents inside Sourcetable, but there’s a whole lot more on the Agentic Web. Superagents are like the conductor that coordinates them all and calls on them when needed. Also, it’s a fun feature name (thanks, Alyssa!)<p>If you remember the linked-data dream of the semantic web movement, that future is now: all of your business data is available and connected in Sourcetable.<p>How does it work? Sourcetable is running a python virtual machine under the hood. Everything is sandboxed, and there are hundreds of AI tools and libraries our AI can access. Superagents are also doing code-gen on the fly to solve problems. The closest system we have found is Replit’s sandboxed operating systems. Beyond that Mixtral, ChatGPT and Anthropic offer some limited data connectivity features, except these AI chat services lack the storage, compute, and code execution that Sourcetable and Replit provide. This is all very new.<p>How is this different to your previous data connectors, etc? We started out using ETL services to sync data and provide a GUI-driven PowerBI like experience in your spreadsheet. This was useful for people who knew SQL and how to write joins to combine fragmented data, but for everyone else (read: practically everyone), this solution just didn’t provide the frictionless, self-serve experience that we wanted.<p>Our choices were to switch the GTM motion or change the product, so we shelved that reporting suite and focused on our AI spreadsheet and waited for models to catch up with our ambitions. Now that they have, we’re re-launching Sourcetable with our original goal in mind: building a spreadsheet-based operating system for the Agent Web, with fully networked data access for <i>everyone</i> on your team.<p>AI is the great UX enabler.<p>Caveats:<p>* We heavily use Postgres, Google Analytics, Stripe and Google Search Console with Superagents.<p>* We haven’t tested every endpoint on the Internet. We find that mainstream, well documented applications work best.<p>* Yes, you can write data back to 3rd party applications and databases. We generally advise against this unless you understand the risks involved in giving AI write-access to your data.<p>Bonus round:<p>* All data connectors added during this launch week are FREE. (Regular AI messaging limits still apply.)<p>Product Feedback? eoin@sourcetable.com